Ori-Mnemos
★ 333
vs
codebase-memory-mcp
★ 47.7k
Ori-Mnemos vs codebase-memory-mcp
Ori-Mnemos: Ori Mnemos is an open-source persistent memory infrastructure for AI agents that implements human cognition models on a knowledge graph. It uses ACT-R decay, spreading activation, and Hebbian learning to manage memory, and achieves state-of-the-art retrieval performance while being zero-infrastructure and portable.; codebase-memory-mcp: codebase-memory-mcp is a structural analysis backend that indexes codebases into a persistent knowledge graph, drastically reducing token usage for code exploration by providing precise structural results. It integrates with AI assistants like Claude Code, offering advanced capabilities such as call graph tracing, architecture overviews, and dead code detection.
01
TL;DR
Ori-MnemosMemory & Context · ★ 333
Multi-hop retrieval QA (e.g., HotpotQA)
codebase-memory-mcpMemory & Context · ★ 47.7k
When to choose:
- Your agent burns tokens searching a medium or large codebase: one graph query replaces many grep and read steps, according to the README.
- You want everything local: a single static binary with no runtime dependencies or API keys.
- You work in many languages and with several coding agents, which the installer configures automatically.
When to skip:
- You do not want an installer to edit your agents' config files and add hooks; the README offers --skip-config to install only the binary.
- You need project decisions and conventions rather than code structure; a scaffold such as mex is closer.
- You are cautious about unsigned binaries: some antivirus engines have flagged the release, which the project documents as a false positive.
02
Side-by-Side Comparison
Field
Ori-Mnemoscodebase-memory-mcpCategory
Memory & Context
Memory & Context
Stars
★ 333
★ 47.7k
License
Apache-2.0
MIT
Install Command
npm install -g ori-memory && ori init my-agent && cd my-agent
curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash
Updated
3w ago
1d ago
Open Source
Yes
Yes
Tags
agent-memory, ai-agent, ai-agents
knowledge-graph, codebase-analysis, AI-assistant-tools
03
Features
Ori-Mnemos01Persistent memory across sessions, clients, and machines
02Knowledge graph with wiki-links, PageRank, and community detection
03Three memory spaces with cognitive forgetting (ACT-R decay)
04Four-signal fusion retrieval (semantic, BM25, PageRank, warmth)
05Retrieval intelligence with Q-learning and meta-learning
codebase-memory-mcp01Indexes a codebase into a persistent knowledge graph using tree-sitter, with semantic type resolution for several major languages
02Supports 150+ languages with grammars compiled into a single static binary
0317 MCP tools: search, call tracing, architecture overview, impact analysis, dead code detection, Cypher queries and more
04Indexes infrastructure-as-code such as Dockerfiles and Kubernetes manifests
05Built-in 3D graph visualisation served locally
04
Use Cases
Ori-Mnemos↳Multi-hop retrieval QA (e.g., HotpotQA)
↳Long-term conversational memory (e.g., LoCoMo)
↳Persistent AI agent identity and knowledge
codebase-memory-mcp↳Code exploration and understanding: Quickly understand codebase architecture, find functions, and trace call paths without high token costs.
↳Impact analysis and refactoring: Map git diffs to affected symbols, detect dead code, and analyze function fan-out to aid refactoring efforts.
↳AI assistant integration: Enhance AI assistants like Claude Code with precise structural queries for more effective code-related questions.
↳Architecture Decision Records management: Store, update, and retrieve architectural decisions directly within the codebase context.
↳Automated scripting and CI/CD: Utilize CLI mode for single-shot graph operations in scripts or CI/CD pipelines.
05
Best For
Ori-Mnemos—
codebase-memory-mcpMost Popular
FAQ
FAQ
What is the difference between Ori-Mnemos and codebase-memory-mcp?
Both Ori-Mnemos and codebase-memory-mcp are in the Memory & Context category. Ori-Mnemos has 333 stars, while codebase-memory-mcp has 47.7k stars.
Which is better, Ori-Mnemos or codebase-memory-mcp?
The best choice depends on your use case. Choose Ori-Mnemos if Multi-hop retrieval QA (e.g., HotpotQA), and codebase-memory-mcp if Code exploration and understanding: Quickly understand codebase architecture, find functions, and trace call paths without high token costs..
Is Ori-Mnemos free or open source?
Yes, Ori-Mnemos is open source on GitHub (Apache-2.0).
Is codebase-memory-mcp free or open source?
Yes, codebase-memory-mcp is open source on GitHub (MIT).
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